Designing Well-Structured Cyclic Pentapeptides Based on Sequence–Structure Relationships

Slough, Diana P.; McHugh, Sean M.; Cummings, Ashleigh E.; Dai, Peng; Pentelute, Bradley L.; Kritzer, Joshua A.; Lin, Yu‐Shan

doi:10.1021/acs.jpcb.8b01747

Cited by 21 publications

(44 citation statements)

References 81 publications

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“…2 D). These NOEs are consistent with types II and II 0 b turn structures at positions 5-6 and 2-3 (24), and these positions match the predicted positions for two type II b turns for P7 (residues 2-3 and 5-6, Fig. 1 A).…”

Section: Resultssupporting

confidence: 82%

“…We found that for small CPs, two dihedral angles, either the f and j angles of the same residue (f i and j i ) or the j angle of one residue and the f angle of the next residue (j i and f iþ1 ), need to change coherently to enable conformational switches. By targeting these essential transitional motions using bias-exchange metadynamics (BE-META) simulations, we can efficiently sample the conformational space of a CP (22)(23)(24). Using this method, we started examining CP sequence-structure relationships with explicit-water molecular dynamics (MD) simulations by gradually substituting Gly residues in cyclo-(GGGGGG) with Val.…”

Section: Introductionmentioning

confidence: 99%

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β-Branched Amino Acids Stabilize Specific Conformations of Cyclic Hexapeptides

Cummings

Miao

Slough

et al. 2019

Biophysical Journal

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Cyclic peptides (CPs) are a promising class of molecules for drug development, particularly as inhibitors of protein-protein interactions. Predicting low-energy structures and global structural ensembles of individual CPs is critical for the design of bioactive molecules, but these are challenging to predict and difficult to verify experimentally. In our previous work, we used explicit-solvent molecular dynamics simulations with enhanced sampling methods to predict the global structural ensembles of cyclic hexapeptides containing different permutations of glycine, alanine, and valine. One peptide, cyclo-(VVGGVG) or P7, was predicted to be unusually well structured. In this work, we synthesized P7, along with a less well-structured control peptide, cyclo-(VVGVGG) or P6, and characterized their global structural ensembles in water using NMR spectroscopy. The NMR data revealed a structural ensemble similar to the prediction for P7 and showed that P6 was indeed much less well-structured than P7. We then simulated and experimentally characterized the global structural ensembles of several P7 analogs and discovered that b-branching at one critical position within P7 is important for overall structural stability. The simulations allowed deconvolution of thermodynamic factors that underlie this structural stabilization. Overall, the excellent correlation between simulation and experimental data indicates that our simulation platform will be a promising approach for designing well-structured CPs and also for understanding the complex interactions that control the conformations of constrained peptides and other macrocycles.

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Section: Resultssupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

β-Branched Amino Acids Stabilize Specific Conformations of Cyclic Hexapeptides

Cummings

Miao

Slough

et al. 2019

Biophysical Journal

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“…Since the late 1990s, using manual design and trial-and-error synthesis, the Gellman group has discovered many peptide 'foldamers,' or rigid linear peptide scaffolds that can be functionalized [91][92][93]. Others, such as the Kritzer group, have pursued linear and cyclic foldamers able to bind to target proteins [94,95]. Despite these successes, extensive exploration of sequence and conformation space has been hindered by the lack of robust computational methods.…”

Section: The Development Of Peptide Macrocycle Design Methods That Yimentioning

confidence: 99%

The emerging role of computational design in peptide macrocycle drug discovery

Mulligan

2020

Expert Opinion on Drug Discovery

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Drug discovery is a laborious process with rising cost per new drug. Peptide macrocycles are promising therapeutics, though conformational flexibility can reduce target affinity and specificity. Recent computational advancements address this problem by enabling rational design of rigidly folded peptide macrocycles. Areas Covered: This review summarizes currently approved peptide macrocycle therapeutics and discusses advantages of mesoscale drugs over small molecules or protein therapeutics. It describes the history, rationale, and state of the art of computational tools, such as Rosetta, that allow the design of rigidly structured peptide macrocycles. The emerging pipeline for designing peptide macrocycle drugs is described, including current challenges in designing permeable molecules that can emulate the chameleonic behavior of natural macrocycles. Prospects for reducing computational cost and improving accuracy with emerging computational technologies are also discussed. Expert opinion: To embrace computational design of peptide macrocycle drugs, we must shift current attitudes regarding the role of computation in drug discovery, and move beyond Lipinski's rules. This technology has the potential to shift failures to earlier in silico stages of the drug discovery process, improving success rates in costly clinical trials. Given the available tools, now is the time for drug developers to incorporate peptide macrocycle design into drug discovery pipelines.

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“…3), which can predict the crystal structures of 17 out of these 20 CPs with backbone RMSD < 1.1 Å, and 8 CPs with backbone RMSD < 0.5Å. Metadynamics with RSFF2 was used recently by Lin and coworkers to study sequence–structure relationships of some simple cyclic hexapeptides [90], and design well-structured cyclic pentapeptides [105]. REMD with RSFF2 has also been used to study α-helical stapled peptides, together with GAFF to describe the non-standard amino acids, giving prediction in excellent agreements with experimental observations [[106], [107], [108]].…”

Section: Peptide Structure Predictionmentioning

confidence: 99%

Applications of Molecular Dynamics Simulation in Structure Prediction of Peptides and Proteins

Geng

Chen

et al. 2019

Computational and Structural Biotechnology Journal

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Compared with rapid accumulation of protein sequences from high-throughput DNA sequencing, obtaining experimental 3D structures of proteins is still much more difficult, making protein structure prediction (PSP) potentially very useful. Currently, a vast majority of PSP efforts are based on data mining of known sequences, structures and their relationships (informatics-based). However, if closely related template is not available, these methods are usually much less reliable than experiments. They may also be problematic in predicting the structures of naturally occurring or designed peptides. On the other hand, physics-based methods including molecular dynamics (MD) can utilize our understanding of detailed atomic interactions determining biomolecular structures. In this mini-review, we show that all-atom MD can predict structures of cyclic peptides and other peptide foldamers with accuracy similar to experiments. Then, some notable successes in reproducing experimental 3D structures of small proteins through MD simulations (some with replica-exchange) of the folding were summarized. We also describe advancements of MD-based refinement of structure models, and the integration of limited experimental or bioinformatics data into MD-based structure modeling.

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Designing Well-Structured Cyclic Pentapeptides Based on Sequence–Structure Relationships

Cited by 21 publications

References 81 publications

β-Branched Amino Acids Stabilize Specific Conformations of Cyclic Hexapeptides

β-Branched Amino Acids Stabilize Specific Conformations of Cyclic Hexapeptides

The emerging role of computational design in peptide macrocycle drug discovery

Applications of Molecular Dynamics Simulation in Structure Prediction of Peptides and Proteins

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